We use six benchmark datasets for different tasks to conduct experiments.
The first one is AG's newshttps://www.di.unipi.it/en/ (denoted as AG), which is a benchmark news topic classification dataset.
The second one is Amazon [1]} (we use the “Electronics” domain), which is a widely used dataset for e-commerce review rating prediction.https://jmcauley.ucsd.edu/data/amazon/
The third one is IMDB [2]}, which is a benchmark movie review rating prediction dataset.https://github.com/nihalb/JMARS
The fourth one is MIND [3]}https://msnews.github.io/, which is an English news dataset that contains news content and users' click behaviors.
We perform two tasks on this dataset, including news topic classification based on news body and news recommendation task based on the relevance between clicked news and candidate news.
The fifth one is the CNN/DailyMail dataset [4]} (denoted as CNN/DM), which is a benchmark abstractive text summarization dataset.
The sixth one is PubMed [5]}, which is a benchmark long document summarization dataset.
The statistics of the six datasets are shown in Table REF .
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